Improving data reliability to support marine pollution assessment according to MSFD Descriptor 8 in the European Seas: the contribution of EMODnet Chemistry

1 Introduction

Under the Water Framework Directive (WFD, 2000/60/EC) (European Commission, 2000) and Marine Strategy Framework Directive (MSFD, 2008/56/EC) (European Commission, 2008) of the European Union (EU), member states must take measures to maintain or achieve ‘good environmental and ecological status’ (GES) in the European seas. The MSFD, in particular, involves regular assessments of the marine environment, setting objectives and targets for reaching GES, establishing monitoring programmes, and putting in place measures to improve the state of marine waters. The MSFD sets out 11 descriptive indicators that are then articulated in a set of assessment criteria and associated indicators that are used to assess environmental status. In addition, the Barcelona Convention (Mediterranean Sea), Bucharest Convention (Black Sea), Helsinki Convention (HELCOM, Baltic Sea), and OSPAR Convention (North-East Atlantic) have protocols, strategic action plans, and monitoring/assessment programs in place to protect these regional seas against pollution (OSPAR Convention, 1992; Black Sea Commission, 2009; United Nations Environment Programme, 2019; Baltic Marine Environment Protection Commission, 2021). Following the implementation of the MSFD in 2008, member states had to develop and follow a common approach in environmental monitoring and assessment at the level of a given marine region or sub-region. Regarding chemical pollution, as an amendment to the WFD and MSFD, Directive 2013/39/EU on priority substances in the field of water policy (European Commission, 2013) sets the environmental quality standards for priority substances, such as heavy metals (e.g. mercury), polycyclic aromatic hydrocarbons (e.g. benzo[a]pyrene), dioxins and dioxin-like compounds, brominated diphenylethers, and pesticides (e.g. heptachlor) in water and biota. In 2017, Commission Decision (EU) 2017/848 (European Commission, 2017) laid down the criteria and methodological standards on GES for marine waters and provided the specifications and standardised methods for monitoring and assessment. Despite progress in legislation, it has been reported that that the degree of coherence with respect to implementing the requirements of the aforementioned directives and protocols is still relatively low (United Nations Environment Programme/Coordinating Unit for the Mediterranean Action Plan, 2017; Tornero Alvarez and Hanke, 2018; Gorjanc et al., 2020).

The assessment of marine pollution at regional and sub-regional scales required by the MSFD and Regional Sea Conventions (RSCs) follows a 6-year cycle (MSFD, 2008/56/EC) and implies the use of data collected by multiple sources. These data may be heterogeneous with respect to sampling protocols, analytical methods, laboratory proficiency, and quality assurance (QA) and quality control (QC) procedures. For several countries, availability of harmonised, comparable, and accessible data and information was an issue of great concern in the first reporting cycle of the MSFD and for the Quality Status Reports, especially for the Mediterranean and Black seas (Gonzalez Fernandez et al., 2014; United Nations Environment Programme/Coordinating Unit for the Mediterranean Action Plan, 2017; Commission on the Protection of the Black Sea Against Pollution, 2019; Lipizer et al., 2021).

In terms of ocean data management, the adoption of the ‘findable, accessible, interoperable, and reusable’ (FAIR) principles (Wilkinson et al., 2016) has led to considerable improvements in data infrastructures and data sharing (Tanhua et al., 2019). Although the use of common metadata sets, common data/metadata formats, and standard vocabularies aims to guarantee interoperability (Vinci et al., 2017; Giorgetti et al., 2020), pollution data for the marine environment are often incomparable and unsuitable for regional/sub-regional assessments owing to the use of different sampling methods, pre-treatment, analytical techniques, and QA/QC procedures, and/or to limited information on QA/QC (Molina Jack et al., 2020). Lack of information or inadequate QA/QC can also mean that data quality is compromised. For instance, based on a comparison between sampling, analytical, and QA protocols adopted by laboratories in the region of the Adriatic and Ionian seas, Berto et al. (Berto et al., 2020) observed that heavy metal data were highly heterogenous, highlighting the need to develop common and harmonised protocols for monitoring procedures to be applied for the assessment of GES.

The European Marine Observation and Data Network (EMODnet¹) was setup in 2009 as part of the Blue Growth strategy (European Commission, 2012) to ensure that European marine data across seven discipline-based themes (bathymetry, biology, chemistry, geology, seabed habitats, human activities, and physics) are easily accessible, interoperable, and free from restrictions on use (Martín Míguez et al., 2019). EMODnet Chemistry is the spatial data infrastructure responsible for providing access to marine chemical data (eutrophication, ocean acidification, contaminant, and marine litter data) (Giorgetti et al., 2018). EMODnet Chemistry adopts the FAIR principles and relies on standards, which were established through SeaDataNet², a Pan-European infrastructure for ocean and marine data management (Schaap and Lowry, 2010). EMODnet Chemistry (phase V, 2021–2023) currently involves more than 30 marine research and monitoring institutes and oceanographic data management experts from 26 countries. Data derive from inputs gathered and collated from national monitoring efforts and research activities from all European coastal states (Giorgetti et al., 2018).

Before EMODnet Chemistry was setup, data availability for Descriptor 8 (contaminants) and Descriptor 9 (contaminants in seafood) of the MSFD was very fragmented. Accordingly, efforts have been made within EMODnet Chemistry to i) overcome data fragmentation among institutes; ii) standardise systems to make data ‘FAIR’; iii) harmonise vocabulary (from the National Environment Research Council (NERC, United Kingdom) Vocabulary Server, NVS³), parameter units, metadata profiles, and dataset formats; iv) identify similar sampling/analytical protocols and common target species between data originators; and v) develop data validation and QC procedures/guidelines. Despite the need to further improve data reliability and comparability (e.g. via thorough and uniform QC procedures by data originators), much progress has been made and EMODnet Chemistry offers the potential to instil a more harmonised approach among institutes, ultimately leading to a data repository that contains dependable and useful information.

In addition to sample-specific metadata (e.g. sample time and location), contaminant data should be associated with comprehensive information on the sampling/analytical methods and QA/QC procedures performed by data originators (i.e. different laboratories). This information is required for further QC checks performed by data management infrastructures (e.g. EMODnet) and is also useful for comparing data from different institutes. Detailed metadata reporting templates to obtain both sample-specific and general information on contaminant measurements in the marine environment have been created by the 1) EU Commission Directorate-General for the Environment (EU DG ENV) (with respect to reporting for the WFD)/European Environment Agency (EEA) (with respect to reporting on the state of the environment) (EIONET data dictionary, https://dd.eionet.europa.eu/datasets/latest/WISE-SoE_WaterQualityICM/tables/DisaggregatedData), 2) International Council for the Exploration of the Sea (ICES) (relating to the OSPAR/Helsinki conventions) (International Council for the Exploration of the Sea, 2015), 3) United Nations Environment Program–Mediterranean Action Plan (UNEP–MAP) (relating to the Barcelona Convention) (United Nations Environment Programme, 2021), and 4) NORMAN Network for emerging contaminants (https://www.norman-network.com/nds/empodat/downloadDCT.php). With the development of EMODnet Chemistry, there has been an emphasis on attempting to align efforts with these organisations, including the supporting information that is collected with contaminant data.

A first set of QA/QC information was collected from institutes participating in EMODnet Chemistry in 2014 using a questionnaire proposed by the Italian Institute for Environmental Protection and Research to obtain information on sampling/analytical methods and QA/QC procedures for contaminants. The questionnaire was pursuant to ISO 17025:2005 (‘General requirements for the competence of testing and calibrating laboratories’), which was, however, updated in 2017 (International Organization for Standardization, 2017). Considering the abovementioned factors along with the increase in data requested for GES assessment, an update/revision of the questionnaire was also needed to improve harmonisation of information and alignment with other initiatives dealing with marine pollution data, ultimately to support the FAIR data principles. With the aims of i) improving the reliability of marine contaminant data for the purpose of GES assessment under the MSFD (i.e. by collecting standardised and harmonised information following consolidated international procedures), ii) identifying improvements to facilitate the FAIR principles and support the implementation of the MSFD, and iii) highlighting the heterogeneities in sampling and analytical methods used by different EU member states, a new EMODnet Chemistry questionnaire was prepared, sent out to participants, and analysed in this study to obtain comprehensive up to date information. First, priorities for non-sample-specific metadata fields in a revised questionnaire (pertaining to contaminants in seawater, sediment, and biota) were determined by comparing the metadata required in the aforementioned data collection templates of the EU DG ENV/EEA, ICES, UNEP–MAP, and NORMAN Network. Then, a revised EMODnet Chemistry questionnaire relating to non-sample-specific metadata fields was created and sent out to participants. The completed questionnaires were subsequently assigned digital object identifiers (DOIs) for use in data submissions to EMODnet Chemistry. Finally, the information from the questionnaires was merged and analysed to determine the main field sampling methods and analytical techniques used for different contaminants to observe differences between laboratories and highlight the importance of having such reference information associated with data.

2 Materials and methods

To take account of practices already adopted by European and global frameworks, including the EEA (https://dd.eionet.europa.eu/datasets/latest/WISE-SoE_WaterQualityICM/tables/DisaggregatedData), ICES (International Council for the Exploration of the Sea, 2015) (i.e. the data management infrastructure for the RSCs of the Baltic Sea (HELCOM) and North East Atlantic Ocean (OSPAR)), UNEP–MAP (United Nations Environment Programme, 2021), and NORMAN (the global network of reference laboratories for the monitoring of emerging environmental substances; https://www.norman-network.com/nds/empodat/downloadDCT.php), documents detailing the metadata requirements (pertaining to reporting on contaminants in water, sediment, and biota) of these organisations were collected and compared. The metadata requirements listed in these different documents were merged and organised to distinguish those i) related to water, sediment, and/or biota, and ii) regarded as mandatory, recommended, or optional by the given organisation. Metadata specific to data on litter or rivers/lakes/reservoirs/groundwater, which are outside the scope of this analysis, and generic metadata fields (e.g. ‘other’) were excluded. To facilitate comparison, metadata fields that had the same or similar labels (i.e. different wording) among organisations were identified, assigned a rephrased metadata term for consistency/comparison, and sorted into groups. Thus, the comparison among metadata requested by the different communities was carried out through a harmonised list and the metadata terms were subsequently ranked first by the number of organisations requiring that information, and then by whether the field was mandatory, recommended, or optional. Finally, the metadata terms referring to non-sample-specific information were highlighted in bold (Table S1).

Based on the above evaluation, a questionnaire was developed to collect information regarding laboratory proficiency, QA protocols, and sampling and analytical procedures from data centres contributing contaminant data to the EMODnet Chemistry marine data management infrastructure. Non-sample-specific metadata fields required by three or four organisations were set as mandatory, while others were set as either mandatory or optional. To facilitate the collection of harmonised information and support compilation, searchable drop-down lists (manual input required when the option was not listed) were included for certain fields. Whenever possible, drop-down lists contained standardised options based on the descriptions/full terms of the vocabularies implemented by the British Oceanographic Data Centre (BODC) as part of the NERC vocabulary server (NVS, e.g. P36 codes for the EMODnet Chemistry chemical target groups, S27 codes for chemical substances, and S04 codes for analytical methods) and adopted by the Pan-European infrastructure for ocean and marine data management (SeaDataNet). The use of consolidated standard vocabularies supports coherence among the metadata and data managed by EMODnet Chemistry. Use of the full terms or descriptions of the NVS vocabularies in the drop-down lists aimed to identify gaps in the current vocabulary (e.g. analytical methods not yet coded) to improve the system.

The questionnaire was sent out to 32 scientific institutions and marine monitoring laboratories in 26 European and neighbouring countries, who represent all of the current institutes contributing contaminant data to EMODnet Chemistry. The questionnaire was sent out via email to the list of contact people of the EMODnet Chemistry network, and these people then forwarded the questionnaires to the laboratory responsible for analysing contaminant data. The compilation of the questionnaire was not mandatory as this was considered an initial phase to ascertain the feasibility of establishing it as a mandatory part of data submissions in the future. As part of EMODnet’s long term strategy of providing access to reliable and accurate data, information on methodological protocols and QA/QC needs to be regularly and systematically updated and made available with contaminant data.

3 Results

3.1 Questionnaire template

Based on the prioritised metadata fields from the templates of the EU DG ENV/EEA, ICES, UNEP–MAP, and NORMAN Network (Table S1), it was found that 19 metadata fields were required by all 4 organisations, of which 10 were mandatory for all 4 organisations. In contrast, 11 and 30 metadata fields were required by 3 and 2 organisations, respectively. Of these 60 metadata fields, 26 fields (9 for 4 organisations, 4 for 3 organisations, and 13 for 2 organisations) referred to non-sample specific information (e.g. country of reporting organisation and analytical methods used for a given determinand) (Table S2).

The questionnaire designed according to the above-mentioned comparison included 65 non-sample-specific metadata fields (9, 4, 13, and 12 fields required by 4, 3, 2, and 1 organisation/s, respectively, plus 27 new fields): 14 related to general laboratory procedure/QA information (collected on the coversheet) and 51 related to each matrix (water, sediment, and biota) in separate sections to obtain comprehensive up to date information from institutes participating in EMODnet Chemistry. Figure 1 displays examples of the metadata fields included on the coversheet and in the seawater section of the questionnaire, and Table S3 lists the transposed fields from the seawater, biota, and sediment sections.

FIGURE 1

Figure 1 Examples of the metadata fields in the questionnaire to obtain non-sample-specific information on contaminants from institutes participating in EMODnet Chemistry. (A) Coversheet completed by OGS and (B) part of the seawater section.

3.2 Questionnaire responses

3.2.1 Number and completeness of responses

Forty-two questionnaires were received from 21 institutes (18 countries, Figure 2) participating in EMODnet Chemistry (summarised in Table S4), which corresponds to a response rate of 66% (i.e. 21/32). As it was not mandatory to complete the questionnaire, this response rate was deemed relatively high, especially considering the time and effort required for its compilation and that institutes do not have the same resources available. Each questionnaire was assigned a DOI to facilitate permanent access of this information. Some institutes included information referring to several laboratories within the same questionnaire; therefore, information was collected from a total of 64 single laboratories, with 46 laboratories providing information on the seawater matrix, 24 on the biota matrix, and 26 on the sediment matrix (Table S4).

FIGURE 2

Figure 2 Map showing the locations and logos of the institutes that completed the EMODnet Chemistry questionnaire.

In general, many of the non-auto-filled optional/non-mandatory fields for the seawater, biota, and sediment sections were not completed, which prevented collection of relevant information such as the analytical method citation and the type of reference material used. In addition, some mandatory fields were not completed, especially regarding the actual limit of detection (LoD) and limit of quantification (LoQ) and the method/formula used to determine the LoQ. To highlight the main similarities and differences between EMODnet Chemistry participants with respect to contaminant metadata, the results presented in this section focus on the general laboratory QA information, determinands reported, and field sampling and analytical methods reported, which were completed in all or most cases.

3.2.2 General laboratory QA information

Table 1 summarises the responses to nine QA questions. The comparison indicates that QA procedures are more consolidated and adopted for the analysis of seawater (adopted by 47.8–100% of laboratories) and sediment (38.5–100%) compared with biota (37.5–87.5%). Despite the variability among the different laboratories, the QA practices reflect an overall good level of proficiency: >87% of respondents reported that laboratory activities are performed by qualified staff and that equipment is properly maintained and calibrated prior to analysis; at least 83% of laboratories have a set of methods specified as acceptable and determine the accuracy, precision, and LoD/LoQ associated with analytical methods; 75.0–84.8% of laboratories routinely run quality control samples; 61.5–75.0% of laboratories record control charts to test bias and reproducibility; >50% of laboratories use certified reference materials; >47% of laboratories are ISO 17025 accredited; and 37.5–47.8% of laboratories have their concentration data controlled by a competent authority.

TABLE 1

Table 1 Summary of the number (and percentage of the total for each matrix in italics) of each response to the coversheet questions (by institute–laboratory; n = 46 for seawater, n = 24 for biota, and n = 26 for sediment).

3.2.3 Determinands reported for seawater, sediment, and biota

Table 2 lists the number of determinands reported in the questionnaires grouped by EMODnet Chemistry target groups (P36 codes, BODC vocabulary). Overall, 395 individual determinands were reported for all matrices (141 for seawater, 284 for sediment, and 232 for biota), which included approximately 90% of the substances included in Directive 2013/39/EU on priority substances in the field of water policy. Of the 395 determinands reported, >50% were either hydrocarbons (13.7%), metals and metalloids (12.7%), pesticides and biocides (10.9%), polychlorinated biphenyls (6.3%), antifoulants (4.1%), or fertilisers (3.3%). Of the 38.7% of determinands not currently included in EMODnet Chemistry target groups, >50% were either perfluorochemicals (20.9%), organobromines (17.6%), or dioxins and furans (13.1%).

TABLE 2

Table 2 Number of determinands reported in questionnaires by their EMODnet Chemistry chemical target group (P36 code) for all matrices, seawater, sediment, and biota.

3.2.4 Field sampling and analytical methods

Table 3 summarises the field sampling methods reported in the questionnaires. Biota samples are collected by eight groups of methods (e.g. nets, by hand, and baited traps), reflecting the numerous different species, whereas seawater samples are mainly collected using discrete water samplers and CTDs, and sediment samples are mainly collected using corers and grabs.

TABLE 3

Table 3 Summary of questionnaire responses regarding field sampling methods reported for biota, seawater, and sediment matrices.

Tables 4A, B summarise the questionnaire responses regarding the analytical methods used for determinands within and outside of the EMODnet Chemistry target groups (P36), respectively (see Tables S5, S6 for full details). For antifoulants, information on 16 determinands were reported by 9 laboratories, who use some kind of gas chromatography. For fertilisers, information on 13 determinands were reported by 27 laboratories, who use 8 different analytical methods, with the main method being colorimetric analysis. For hydrocarbons, 54 determinands were reported by 15 laboratories, who use some kind of gas chromatography or high-performance liquid chromatography. For metals and metalloids, 50 determinands were reported by 17 laboratories, who use 12 different analytical methods, mainly inductively coupled plasma mass spectrometry or some kind of atomic absorption spectrometry. For pesticides and biocides, 43 determinands were reported by 11 laboratories, who use either gas chromatography or liquid chromatography/mass spectrometry. For polychlorinated biphenyls, 25 determinands were reported by 9 laboratories, who use some kind of gas chromatography (Table 4A). For determinands outside of the P36 groups, the main chemical groups were perfluorochemicals (32 determinands reported by 5 laboratories), organobromines (27 determinands reported by 8 laboratories), dioxins (20 determinands were reported by 6 laboratories), and organochlorines (12 determinands reported by 9 laboratories), all of which are analysed using some kind of gas chromatography or liquid chromatography (Table 4B). Overall, 17 different kinds of gas chromatography and liquid chromatography, and 10 different kinds of spectrometry were reported in the questionnaires (Table S6).

TABLE 4A

Table 4A Questionnaire responses regarding the analytical methods used for determinands within the main EMODnet Chemistry chemical target groups (i.e. P36 codes).

3.2.5 LoQs

The questionnaire allowed information on the LoQs of different substances to be collected, which is a mandatory requirement for the EU DG ENV/EEA, ICES, UNEP–MAP, and NORMAN Network (Table S2). Information on the method or formula used to calculate the LoQ was also requested in the questionnaire as this information is useful for determining data comparability. Various methods were reported for determining the LoQ and full details of the LoD/LoQ information reported can be found in the questionnaires (available upon request). Here, a few examples are taken to highlight some inter-laboratory/inter-instrument variations for the same substances. As shown in Figure 3A and Table S7, there was up to three orders of magnitude difference between the LoQs reported for pyrene in seawater between different laboratories for the same analytical method (gas chromatography–mass spectrometry; 0.00002–0.01 µg/L) and an order of magnitude of difference between analytical methods (0.004 µg/L for high-performance liquid chromatography–ultraviolet detector versus 0.01 µg/L for gas chromatography–mass spectrometry). For lead in sediment (Figure 3B; Table S7), the reported LoQs ranged from 0.0002 mg/kg to 25.4 mg/kg, including a range of 0.03–6.0 mg/kg for the same analytical method (atomic absorption spectrometry - graphite furnace). Similarly, for anthracene in biota, the LoQs of laboratories using the same analytical method (gas chromatography–mass spectrometry) ranged from 0.11 µg/kg to 10.0 µg/kg (Figure 3C; Table S7).

FIGURE 3

Figure 3 Examples of the limit of quantification (LoQ) values reported in the questionnaires to illustrate inter-laboratory and inter-instrument differences for (A) pyrene in seawater, (B) lead in sediment, and (C) anthracene in biota. See Table S5 for more information.

4 Discussion

The adoption of standard data and metadata models along with the systematic collection and provision of detailed information on methods, laboratory performance, and QA/QC procedures all contribute to the process of data curation, which emerges as a key data management process when there is an increase in the number of data sources and platforms for data generation (Freitas and Curry, 2016; Yoon et al., 2022). Especially in the field of environmental sciences, improvements in data curation require a multidisciplinary approach that involves information, communication, and technology (ICT) experts, multidisciplinary marine environmental scientists in charge of data acquisition, and authorities responsible for environmental status assessment. This approach may be greatly supported by strengthening collaboration and dialogue between data managers, data originators, and data users. In this regard, the activities described in this study are the result of a large effort combining (a) requirements in terms of data and metadata from the MSFD community and RSCs, (b) tools and protocols for data management adopted within the EMODnet framework, and (c) information from the laboratories in charge of analysing samples and generating contaminant data.

Based on the templates proposed by several European and global frameworks, the new EMODnet Chemistry questionnaire allowed a rich set of standardised and harmonised information that is required to evaluate data comparability and, therefore, re-usability (Wilkinson et al., 2016) to be collected from 64 laboratories in 18 European countries. Data comparability refers to the possibility to use data from multiple sources and is assisted by information on methodological aspects (from sampling to analysis and laboratory performance) that is available to data users, who can evaluate whether possible methodological heterogeneity may prevent the use of data from different sources. The collection of information through this questionnaire is part of a systematic effort that initially began in 2014 when the first EMODnet questionnaire was sent out to institutes participating in EMODnet Chemistry, thus contributing to EMODnet’s long-term strategy of providing access to reliable and accurate information.

Importantly, the use of DOIs makes the EMODnet questionnaires openly available and associates them with data submitted to EMODnet Chemistry, allowing different data users to evaluate data comparability, and improving transparency in data quality, reliability, and fitness for use for assessment purposes. Such transparency is crucial for environmental status assessment in cross-border areas (e.g. at regional and sub-regional scales), as required under the MSFD and by RSCs, whereby data from multiple and heterogeneous sources are needed. The contaminants reported in the questionnaires included approximately 90% of the substances included in Directive 2013/39/EU on priority substances in the field of water policy (European Commission, 2013). Considering that these substances are used to assess marine pollution according to Descriptor 8 of the MSFD, it is essential to collect and evaluate QA/QC information from different laboratories.

Evaluation of the questionnaires highlighted some heterogeneities in laboratory proficiency, analytical techniques, and methods used to calculate the LoQ. Although the questionnaire responses regarding QA procedures indicate an overall good level of laboratory proficiency (Table 1), they also suggest possible improvements. For instance, although 100% of laboratories reported that they have properly qualified people performing laboratory activities for seawater and sediment samples, only 47.8%, 54.2%, and 53.8% of laboratories are ISO 17025 accredited for seawater, sediment, and biota analysis, respectively, and only 60.9%, 50.0%, and 57.7% of laboratories use certified reference materials when analysing contaminant concentrations in seawater, biota, and sediment samples, respectively.

In terms of analytical methods (Section 3.2.3), the results indicate general harmonisation between the laboratories participating in EMODnet Chemistry for hydrocarbons (gas chromatography or high-performance liquid chromatography), antifoulants (some kind of gas chromatography), pesticides and biocides (gas chromatography or liquid chromatography/mass spectrometry), and polychlorinated biphenyls (some kind of gas chromatography). However, 8 different analytical methods were reported for fertilisers (i.e. nitrogen and phosphorus substances) and 12 different analytical methods were reported for metals and metalloids, suggesting the potential for increased harmonisation.

Inter-laboratory/inter-instrument variations in the reported LoQs and LoDs for a given substance were expected and occur because of various factors, such as the analytical technique/instrument used, method used to calculate these values, and accuracy of the calibration curve obtained. In addition, it is also possible that compilation errors could have occurred (e.g. selecting the wrong unit or providing the LoD method instead of the requested LoQ method) due to the complexity of information requested and the expertise required to fill in the questionnaire. Although IUPAC made international recommendations for calculating LoDs and LoQs in 1995 (Currie, 1995), problems (e.g. that there are several possible conceptual approaches to the subject, as confirmed by the examples included in Table S7) associated with the subject of the LoD and LoQ were already outlined by IUPAC in 2002 (Thompson et al., 2002) and are also considered elsewhere (Barwick, 2023). While laboratory proficiency and equipment depend on institutional resources that may differ among countries, improved coherence in LoD/LoQ calculation methods could be a step towards improved harmonisation. Accordingly, the results of the questionnaires suggest that it could be beneficial to recommend and share IUPAC’s LoD/LoQ calculation methods between EMODnet participating laboratories.

It is fundamental to understand the complexity and entire cycle of pollution data (from in situ sampling to analytical procedures, QA/QC protocols, and data curation) and to have access to accurate and updated metadata and methodological information to allow a coherent assessment of marine environmental status and, ultimately, to take proper actions to limit pollution. This work further extends the approach already proposed for heavy metals in a sub-basin of the Mediterranean Sea (Berto et al., 2020; Molina Jack et al., 2020) by addressing more chemical groups and providing information for all European Seas.

Lastly, even though drop-down lists were included in the questionnaire to facilitate the collection of standard information and to avoid spelling mistakes and the use of wrong terms or variations in the same term for important metadata fields, the issues of typos and incomplete information were still observed for information requiring manual input, representing possible sources of error and inconsistency given the many different countries involved.

5 Conclusions

In this work, rich standardised and harmonised QA/QC information on contaminants was collected at the European level using a dedicated questionnaire, including information requested by different RSCs and legal frameworks (e.g. WFD and MSFD). Overall, the questionnaire allows standard information to be collected and made available, and promotes interoperability among data infrastructures, thus supporting the FAIR data principles. The information received from 64 laboratories associated with 21 institutes in 18 countries i) highlights disparities in the entire process of contaminant data production, ii) identifies gaps in existing vocabulary terms used to code contaminants, and iii) supports action to be taken to improve the overall data management system. In particular, high levels of heterogeneity were observed in the analytical methods and with respect to performance in terms of LoQs for some substances; however, such heterogeneity could also be due to some compilation errors, highlighting the need for more care to be taken to provide correct information, which will be addressed in a future amended questionnaire. The questionnaire contributes to the need for accurate and comprehensive metadata to improve the reliability of marine contaminant data collected under the MSFD. As a target of improved harmonisation, IUPAC’s methods for calculating LoD/LoQ values could be shared within the EMODnet network, which involves 26 European and neighbouring countries. This contribution also highlights the attention, effort, and expertise required to carry out data curation, which is crucial to support a reliable assessment of marine pollution, and ultimately better management of the marine environment. Data curation is still an overlooked aspect of the overall scientific research process and requires multidisciplinary expertise, dedicated staff, and funding. The support provided by EMODnet to the implementation of the MSFD is an ongoing process, whereby those involved learn by doing and the system improves over time.

Lastly, as the EMODnet network also involves countries beyond the EU (e.g. Montenegro, Georgia, and Turkey), the activity described in this study allowed standardised and harmonised information to be collected from institutions outside the EU. Further, the study promotes the sharing of a common understanding on the importance of accurate metadata and QA/QC details. Access to harmonised information represents an important step towards interoperability and FAIRness with respect to pollution data, which are of paramount importance to support the principles of coordinated ecosystem-based management, also at the transboundary level.

Data availability statement

The original contributions presented in the study are included in the article/Supplementary material, further inquiries can be directed to the corresponding author/s.

Ethics statement

Ethical approval was not required for the studies involving humans because it was not applicable to the nature of this study. The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study. This study was performed as part of the European Marine Observation and Data Network (EMODnet Chemistry) contract between the National Institute of Oceanography and Applied Geophysics (OGS, the coordinating institution) and European Union Executive Agency for SMEs (EASME). All questionnaires were completed by institutes participating in EMODnet Chemistry. This contract requires that (1) data must be free of charge and free of restrictions of use, including in relation to pre-existing rights; and (2) data and data products shall be accompanied by metadata covering at least: (a) ownership; (b) assessment of accuracy and precision according to pre-existing standards in the marine field; and (c) indication of method used for their measurement or construction. Prior to manuscript submission, written consent regarding the publication of either i) laboratory name/s and institute name, ii) institute name only, or iii) country name only was obtained from each institution that completed a questionnaire.

Author contributions

MF: Data curation, Formal analysis, Methodology, Visualization, Writing – original draft, Writing – review & editing. ML: Conceptualization, Supervision, Writing – original draft, Writing – review & editing.

Funding

The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This work was supported by EMODnet Chemistry Phase 5 (2021–2023, funded by EASME/2020/OP/0006), coordinated by Alessandra Giorgetti (OGS).

Acknowledgments

We acknowledge the following contributions of completing the questionnaires: Aarhus University, Danish Centre for Environment and Energy (AU-DCE) (Denmark); Balearic Islands Coastal Observing and Forecasting System (SOCIB) (Spain); Bulgarian National Oceanographic Data Centre, Institute of Oceanology (IO-BAS) (Bulgaria); Flanders Marine Institute (VLIZ) (Belgium); Flanders Research Institute for Agriculture, Fisheries and Food (ILVO) (Belgium); Finnish Environment Institute (SKYE) (Finland); French Research Institute for the Exploitation of the Sea (IFREMER) (France); Hellenic Centre for Marine Research, Institute of Oceanography (HNODC-HCMR) (Greece); Hydrographic Institute (IH) (Portugal); Institute of Marine Biology (IMBK) (Montenegro); Institute of Oceanography and Fisheries (IOR) (Croatia); Iv. Javakhishvili Tbilisi State University, Centre of Relations with UNESCO Oceanological Research Centre and GeoDNA (TSU-DNA) (Georgia); Latvian Institute of Aquatic Ecology (LHEI) (Latvia); National Institute for Marine Research and Development (NIMRD) (Romania); National Institute of Biology (NIB), Marine Biology Station (Slovenia); National Institute of Oceanography and Applied Geophysics (OGS), Division of Oceanography (Italy); National Research Council (CNR) (Italy); Royal Belgian Institute of Natural Sciences, Operational Directorate Natural Environment, Belgian Marine Data Centre (RBINS-BMDC) (Belgium); Swedish Meteorological and Hydrological Institute (SMHI) (Sweden); Tallinn University of Technology - Marine Systems Institute (TalTech-MSI) (Estonia); Istanbul University, Institute of Marine Science and Management (IU-IMSM) (Turkey).

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Supplementary material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fmars.2023.1275097/full#supplementary-material

Abbreviations

BODC, British Oceanographic Data Centre; DOI, Digital object identifier; EEA, European Environment Agency; EMODnet, European Marine Observation and Data Network; EU, European Union; EU DG ENV, EU Commission Directorate-General for the Environment; FAIR, Findable, accessible, interoperable, and reusable; GES, Good environmental and ecological status; HELCOM, Helsinki Convention; ICES, International Council for the Exploration of the Sea; LoD, Limit of detection; LoQ, Limit of quantification; MSFD, Marine Strategy Framework Directive; NVS, National Environment Research Council (NERC) Vocabulary Server; QA/QC, Quality assurance/quality control; RSCs, Regional Sea Conventions; UNEP–MAP, United Nations Environment Program–Mediterranean Action Plan; WFD, Water Framework Directive.

Footnotes

1. ^ https://emodnet.ec.europa.eu/en.
2. ^ SeaDataNet - SeaDataNet.
3. ^ NVS (nerc.ac.uk).

References

Baltic Marine Environment Protection Commission (2021) Baltic Sea Action Plan: 2021 Update. Available at: https://helcom.fi/wp-content/uploads/2021/10/Baltic-Sea-Action-Plan-2021-update.pdf (Accessed June 20, 2023).

Google Scholar

Barwick V. J. (2023) Eurachem Guide: Terminology in Analytical Measurement – Introduction to VIM 3 (Eurachem). Available at: www.eurachem.org (Accessed June 20, 2023).

Google Scholar

Berto D., Formalewicz M., Giorgi G., Rampazzo F., Gion C., Trabucco B., et al. (2020). Challenges in harmonized assessment of heavy metals in the adriatic and ionian seas. Front. Mar. Sci. 7. doi: 10.3389/fmars.2020.00717

CrossRef Full Text | Google Scholar

Black Sea Commission (2009). Implementation of the Strategic Action Plan for the Rehabilitation and Protection of the Black Sea (2002–2007). (Istanbul, Turkey: Publications of the Commission on the Protection of the Black Sea Against Pollution (BSC), 2009-1), 252 pp.

Google Scholar

Commission on the Protection of the Black Sea Against Pollution (2019) State of the Environment of the Black Sea, (2009-2014/5) (Istanbul, Turkey: Commission on the Protection of the Black Sea Against Pollution). Available at: http://www.blacksea-commission.org/Inf.%20and%20Resources/Publications/SOE2014/ (Accessed June 20, 2023).

Google Scholar

Currie L. A. (1995). Nomenclature in evaluation of analytical methods including detection and quantification capabilities (IUPAC recommendations 1995). Pure. Appl. Chem. 67 (10), 1699–1723. doi: 10.1351/pac199567101699

CrossRef Full Text | Google Scholar

EIONET data dictionary. Available at: https://dd.eionet.europa.eu/datasets/latest/WISE-SoE_WaterQualityICM/tables/DisaggregatedData (Accessed June 20, 2023).

Google Scholar

EMODnet. Available at: https://emodnet.ec.europa.eu/en (Accessed July 30, 2023).

Google Scholar

European Commission (2000) Directive 2000/60/EC of the european Parliament and of the Council of 23 October 2000 Establishing a Framework for Community Action in the Field of Water Policy. Available at: http://data.europa.eu/eli/dir/2000/60/2014-11-20.

Google Scholar

European Commission (2008) Directive 2008/56/EC of the European Parliament and of the Council of 17 June 2008 Establishing a Framework for Community Action in the Field of Marine Environmental Policy (Marine Strategy Framework Directive). Available at: http://data.europa.eu/eli/dir/2008/56/2017-06-07 (Accessed June 20, 2023).

Google Scholar

European Commission (2012) GREEN PAPER Marine Knowledge 2020 from Seabed Mapping to Ocean Forecasting. Available at: https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:52012DC0473 (Accessed June 20, 2023).

Google Scholar

European Commission (2013) Directive 2013/39/EU of the European Parliament and of the Council of 12 August 2013 Amending Directives 2000/60/EC and 2008/105/EC as Regards Priority Substances in the Field of Water Policy. Available at: http://data.europa.eu/eli/dir/2013/39/oj (Accessed June 20, 2023).

Google Scholar

European Commission (2017) Commission Decision (EU) 2017/848 of 17 May 2017 Laying down Criteria and Methodological Standards on Good Environmental Status of Marine Waters and Specifications and Standardised Methods for Monitoring and Assessment, and Repealing Decision 2010/477/EU. Available at: http://data.europa.eu/eli/dec/2017/848/oj (Accessed June 20, 2023).

Google Scholar

Freitas A., Curry E. (2016). “Big Data Curation,” in New Horizons for a Data-Driven Economy (Switzerland: Springer International Publishing AG), 87–118. doi: 10.1007/978-3-319-21569-3

CrossRef Full Text | Google Scholar

Giorgetti A., Lipizer M., Molina Jack M. E., Holdsworth N., Mose Jensen H., Buga L., et al. (2020). Aggregated and validated datasets for the european seas: the contribution of EMODnet chemistry. Front. Mar. Sci. 7. doi: 10.3389/fmars.2020.583657

CrossRef Full Text | Google Scholar

Giorgetti A., Partescano E., Barth A., Buga L., Gatti J., Giorgi G., et al. (2018). EMODnet chemistry spatial data infrastructure for marine observations and related information. Maritime. Spatial. Planning. Ecosystem. Approach. Supporting. Inf. Syst. (MapSIS. 2017). 166, 9–17. doi: 10.1016/j.ocecoaman.2018.03.016

CrossRef Full Text | Google Scholar

Gonzalez Fernandez D., Coughlan C., Stips A., Hanke G., Palialexis A.. (2018). EMODnet chemistry spatial data infrastructure for marine observations and related information. Maritime. Spatial. Planning. Ecosystem. Approach. Supporting. Inf. Syst. (MapSIS. 2017). 166, 9–17. doi: 10.1016/j.ocecoaman.2018.03.016

CrossRef Full Text | Google Scholar

Gorjanc S., Klančnik K., Murillas-Maza A., Uyarra M. C., Papadopoulou N. K., Paramana Th., et al. (2020). Coordination of pollution-related MSFD measures in the mediterranean - where we stand now and insights for the future. Mar. pollut. Bull. 159, 111476. doi: 10.1016/j.marpolbul.2020.111476

PubMed Abstract | CrossRef Full Text | Google Scholar

International Council for the Exploration of the Sea (2015) Environmental Reporting Format (ERF) Version 3.2.5. Available at: https://www.ices.dk/data/tools/Pages/Data-formats.aspx (Accessed June 20, 2023).

Google Scholar

International Organization for Standardization (2017). ISO/IEC 17025 - Testing and Calibration Laboratories (Geneva Switzerland: International Organization for Standardization, ISO Central Secretariat).

Google Scholar

Lipizer M., Molina Jack M. E., Lorenzon S., Giorgi G., Manfra L., Trabucco B., et al. (2021). “Harmonization Requirements for MSFD and EcAp (Contaminants) in the ADRION Region: From Sampling to Data Visualization,” in The Montenegrin Adriatic Coast: Marine Chemistry Pollution. Eds. Joksimović D., Đurović M., Zonn I. S., Kostianoy A. G., Semenov A. V. (Cham: Springer International Publishing), 415–429. doi: 10.1007/698_2020_719

CrossRef Full Text | Google Scholar

Martín Míguez B., Novellino A., Vinci M., Claus S., Calewaert J.-B., Vallius H., et al. (2019). The european marine observation and data network (EMODnet): visions and roles of the gateway to marine data in europe. Front. Mar. Sci. 6. doi: 10.3389/fmars.2019.00313

CrossRef Full Text | Google Scholar

Molina Jack M. E., Bakiu R., Castelli A., Čermelj B., Fafanđel M., Georgopoulou C., et al. (2020). Heavy metals in the adriatic-ionian seas: A case study to illustrate the challenges in data management when dealing with regional datasets. Front. Mar. Sci. 7. doi: 10.3389/fmars.2020.571365

CrossRef Full Text | Google Scholar

National Environment Research Council (NERC) Vocabulary Server (NVS) NVS (nerc.ac.uk) (Accessed July 30, 2023).

Google Scholar

NORMAN Network. Available at: https://www.norman-network.com/nds/empodat/downloadDCT.php (Accessed June 20, 2023).

Google Scholar

OSPAR Convention (1992) Convention for the protection of the marine environment of the north-east Atlantic. Available at: https://www.ospar.org/convention/text (Accessed June 20, 2023).

Google Scholar

Palialexis A., Tornero V., Barbone E., González Fernández D., Hanke G., Cardoso A., et al. (2014). In-depth assessment of the EU member states’ Submissions for the marine strategy framework directive under articles 8, 9 and 10. doi: 10.2788/64014

CrossRef Full Text | Google Scholar

Schaap D. M. A., Lowry R. K. (2010). SeaDataNet – pan-european infrastructure for marine and ocean data management: unified access to distributed data sets. Int. J. Digital. Earth 3 (sup1), 50–69. doi: 10.1080/17538941003660974

CrossRef Full Text | Google Scholar

SeaDataNet. Available at: https://www.seadatanet.org (Accessed July 30, 2023).

Google Scholar

Tanhua T., Pouliquen S., Hausman J., O’Brien K., Bricher P., Taco de Bruin, et al. (2019). Ocean FAIR data services. Front. Mar. Sci. 6. doi: 10.3389/fmars.2019.00440

CrossRef Full Text | Google Scholar

Thompson M., Ellison S. L. R., Wood R. (2002). Harmonized guidelines for single-laboratory validation of methods of analysis (IUPAC technical report). Pure. Appl. Chem. 74 (5), 835–855. doi: 10.1351/pac200274050835

CrossRef Full Text | Google Scholar

Tornero Alvarez M., Hanke G (2018). Marine chemical contaminants – support to harmonized MSFD reporting: Substances considered for MSFD descriptor 8. (Luxembourg: Publications Office of the European Union). doi: 10.2760/804610

CrossRef Full Text | Google Scholar

United Nations Environment Programme (2019) Convention for the protection of the Marine Environment and the Coastal Region of the Mediterranean and Its Protocols (Nairobi). Available at: https://wedocs.unep.org/bitstream/handle/20.500.11822/31970/bcp2019_web_eng.pdf (Accessed June 20, 2023).

Google Scholar

United Nations Environment Programme (2021) UNEP/MED WG.492/8: Monitoring Guidelines/Protocols for Analytical Quality Assurance and Reporting of Monitoring Data for IMAP Common Indicators 13, 14, 17, 18 and 20. Available at: https://wedocs.unep.org/bitstream/handle/20.500.11822/35980/21wg492_08_eng.pdf?sequence=1 (Accessed June 20, 2023).

Google Scholar

United Nations Environment Programme/Coordinating Unit for the Mediterranean Action Plan (2017) Quality Status Report for the Mediterranean – MED QSR 2017 (United Nations Environment Programme/Coordinating Unit for the Mediterranean Action Plan Barcelona Convention Secretariat). Available at: https://www.unep.org/unepmap/resources/quality-status-report-mediterranean-med-qsr-2017 (Accessed June 20, 2023).

Google Scholar

Vinci M., Giorgetti A., Lipizer M. (2017). The Role of EMODnet chemistry in the european challenge for good environmental status. Nat. Hazards. Earth Syst. Sci. 17 (2), 197–204. doi: 10.5194/nhess-17-197-2017

CrossRef Full Text | Google Scholar

Wilkinson M. D., Dumontier M., Jan Aalbersberg I. J., Appleton G., Axton M., Baak A., et al. (2016). The FAIR guiding principles for scientific data management and stewardship. Sci. Data 3, 160018–160018. doi: 10.1038/sdata.2016.18

PubMed Abstract | CrossRef Full Text | Google Scholar

Yoon A., Kay J., Donaldson D. R. (2022). Big data curation framework: curation actions and challenges. J. Inf. Sci. 0(0), 01655515221133528. doi: 10.1177/01655515221133528

CrossRef Full Text | Google Scholar